GreenSlot: scheduling energy consumption in green datacenters

  • Authors:
  • Íñigo Goiri;Kien Le;Md. E. Haque;Ryan Beauchea;Thu D. Nguyen;Jordi Guitart;Jordi Torres;Ricardo Bianchini

  • Affiliations:
  • UPC/BSC and Rutgers Univ.;Rutgers University;Rutgers University;Rutgers University;Rutgers University;UPC/BSC;UPC/BSC;Rutgers University

  • Venue:
  • Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
  • Year:
  • 2011

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Abstract

In this paper, we propose GreenSlot, a parallel batch job scheduler for a datacenter powered by a photovoltaic solar array and the electrical grid (as a backup). GreenSlot predicts the amount of solar energy that will be available in the near future, and schedules the workload to maximize the green energy consumption while meeting the jobs' deadlines. If grid energy must be used to avoid deadline violations, the scheduler selects times when it is cheap. Our results for production scientific workloads demonstrate that Green-Slot can increase green energy consumption by up to 117% and decrease energy cost by up to 39%, compared to a conventional scheduler. Based on these positive results, we conclude that green datacenters and green-energy-aware scheduling can have a significant role in building a more sustainable IT ecosystem.